Executing, Comparing, and Reusing Linked Data-Based Recommendation Algorithms With the Allied Framework

摘要: Data published on the Web following Linked principles has resulted in a global data space called of Data. These led to semantically interlink and connect different resources at level regardless their structure, authoring, location, etc. The tremendous continuous growth also implies that now it is more likely find describe real-life concepts. However, discovering recommending relevant related still an open research area. This chapter studies recommender systems use as source containing significant amount available relationships useful produce recommendations. Furthermore, presents framework deploy execute state-of-the-art algorithms for have been re-implemented measure benchmark them application domains without being bound unique dataset.